Cloud-Based Three-Dimensional Pattern Analysis and Classification of Proximal Humeral Fractures – A Feasibility Study

6 pages•Published: December 13, 2022

Denise Baumann, Ariane Gerber Popp, Markus Degen, Dominique Brodbeck, Florian Coigny, Thomas Suter and Erik Schkommodau

Abstract

For the complex clinical issue of treatment decision for proximal humeral fractures, dedicated software based on three-dimensional (3D) computer tomography (CT) models would potentially allow for a more accurate fracture classification and help to plan the surgical strategy needed to reduce the fracture in the operating theatre. The aim of this study was to elaborate the feasibility of implementation of such software using state-of-the-art cloud technology to enable access to its functionalities in a distributed manner. Feasibility was studied by implementation of a prototype application, which was tested in a usability study with five biomedical engineers.
Implementation of a cloud-based solution was feasible using state-of-the-art technology under application of a specific software architectural approach allowing to distribute computational load between client and server. Mean System Usability Scale (SUS) Score for the developed application was determined to be 63 (StDev 20.4). These results can be interpreted as a medium low usability with high standard deviation of the measured SUS score. We conclude that more test subjects should be included in future studies and the developed application should be evaluated with a representative user group such as orthopaedic shoulder surgeons in a clinical setting.

Keyphrases: classification of proximal humeral fractures, cloud based software as a service, surgical decision support, three dimensional pattern analysis of proximal humeral fractures

In: Ferdinando Rodriguez Y Baena, Joshua W Giles and Eric Stindel (editors). Proceedings of The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 5, pages 25-30.

Links:	https://easychair.org/publications/paper/M9Gr
	https://doi.org/10.29007/bprl

BibTeX entry

@inproceedings{CAOS2022:Cloud_Based_Three_Dimensional,
  author    = {Denise Baumann and Ariane Gerber Popp and Markus Degen and Dominique Brodbeck and Florian Coigny and Thomas Suter and Erik Schkommodau},
  title     = {Cloud-Based Three-Dimensional Pattern Analysis and Classification of Proximal Humeral Fractures – A Feasibility Study},
  booktitle = {Proceedings of The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Ferdinando Rodriguez Y Baena and Joshua W Giles and Eric Stindel},
  series    = {EPiC Series in Health Sciences},
  volume    = {5},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/M9Gr},
  doi       = {10.29007/bprl},
  pages     = {25-30},
  year      = {2022}}

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